The Relationship between Customer's Personal Characteristics and Usage of Electronic Banking Services

Authors

  • Aram Heidari Payam e Noor University of Sanandaj, Iran
  • Nadia Asady SAM Consulting Engineers

DOI:

https://doi.org/10.21928/juhd.v2n3y2016.pp498-501

Keywords:

Data mining, clustering, e-banking

Abstract

Nowadays, data is the heart of business processes of small and large companies, such as retailers, communication, production, facilities, transportation, insurance, credit cards and banking. Hence, there is a need for a tool that can process stored data and provide users with the information obtained from this process. In this context, data mining is one of many scientific branches that in recent years has experienced a rapid expansion worldwide. Data mining is the process of discovering knowledge (that is) hidden in data, which by describing, explaining, predicting and controlling various phenomena, has a wide application in various fields. The main idea of ​​data mining is based on the fact that old data contain information that can be used in the future and will be valuable. The purpose of data mining is to find those patterns in existing data that make the needs, preferences and desires of the business clearer. Therefore, extracting the symptoms from useless things, i.e. identifying underlying patterns within seemingly random variables, is one of the important roles of data mining. The aim of this paper is to analyze the relationship between individual characteristics of the client and the use of electronic banking services (using data mining methods).

References

[1] Salehi Sedghiani, J. and Sarvarnezhad, S., "determine new strategies for banking in the adoption of mobile banking service users in private banks" , Strategic Management Studies, pp. 39-57, No. 6, Summer 2011
[2] Akbarpour Shirazy, M. and Toopchy, Hussein, "Data Mining: Concepts, Methods and Applications", University of K-N,2012
[3] Eman M. Ali, Ahmed F.Seddik, and Mohammad Haggag, "data mining techniques", Journal of Biomedical Engineering No. 131, of 11 February 2012,
[4] Bahrami Zennor, Maryam, "Data Mining: discover hidden knowledge data", Persian date Farvardin, 2010
[5] Jalali talab, Atoosa. Bozorgzadeh, Sanaz, "a data mining application using weka", University of Science and Technology, the summer of 2010
[6] Kazemi, M., Kurd, Bagher, and Mehrvarzy, Muhammad, "Key Factors for successful internet services and providing a predictive model using decision tree", Research Management, pp. 29-45, Issue I, winter 2010
[7] Shahrabi, Jamal, "data mining book," Research Institute of Amir Kabir University of Gita and data processing, printing, 2007
[8] Soltani, K., "Data Mining with weka", Network Magazine, Issue 122, Persian date May 2011
[9] Shahraki, Alireza and Pourghassem, Alireza, "Data mining, a powerful tool in improving organizational intelligence", the first national conference on business intelligence, 29 and 30 Persian date October 2010.

Published

2016-08-31

Issue

Section

Articles